Supply chain equilibrium and transportation network efficiency based on MSA algorithms and multilayer decision model

2019 ◽  
Vol 37 (1) ◽  
pp. 193-204
Author(s):  
Xiaoxun Ouyang ◽  
Yuqin Dai
2022 ◽  
Author(s):  
Qiang Lai ◽  
Hong-hao Zhang

Abstract The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.


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